1. Field of the Invention
The present invention relates to a method and apparatus to enhance digital image quality, and more particularly, to a method and apparatus to enhance digital image quality by which a document image obtained by scanning a document including a combination of a text and an image is segmented into a text area, a background area, a halftone image area, and a continuous tone image area and then an image quality of each of the areas is properly enhanced to obtain an improved image quality print.
2. Description of the Related Art
In general, interest in a technique to effectively express an original document using only black and white binary information has increased with the advancement of copying machines, facsimiles, or multi-function peripherals. The technique can be greatly classified into a dithering technique to express actual continuous brightness as pseudo brightness using the spatial black and white distribution of an image document and a bi-level segmentation technique to properly segment a text document into a text and a background to easily read the text from the text document.
However, these techniques are not effective for a document including a combination of a text and an image. In other words, in the bi-level segmentation technique, problems, such as false contours, occur in an image, and in the dithering technique, the pseudo brightness smoothes the edge of an image, which deteriorates the reading of a text portion. In order to solve these problems, a variety of studies on the enhancement of the image quality of a document including a text and an image are in progress.
FIG. 1 is a flowchart illustrating a conventional method of enhancing the image quality of a document including a combination of a text and an image, the method being disclosed in U.S. Pat. No. 6,175,425, entitled “Document Imaging System for Autodiscrimination of Text and Images,” issued to Ramin Khorram on Jan. 16, 2001. Referring to FIG. 1, the method includes: receiving a multi-valued signal to represent a document image input from a scanner or another input device in operation 100, using a high-pass filter (HPF) to create a template, which defines a high contrast area in a document in operation 102, segmenting the document image into a text area and an image area in operation 104, enhancing an image in the text area by using the HPF in the text area in operation 106, enhancing an image in the image area by using a low-pass filer (LPF) in the image area in operation 108, creating an image to be printed by connecting the image in the text area to the image in the image area in operation 110, halftone-processing the image to be printed in operation 112, and printing a halftone image in operation 114.
In the above-mentioned method, an input document image is segmented into blocks, and then the HPF is used in each of the blocks to classify the blocks into the text area containing a large number of high-band components and the image area containing a small number of high-band components. Thus, if two adjacent blocks belong to different areas, one block may be blocked from the other block. Also, a block has to be very small so that all pixels in the block belong to the same area. However, as the block is small, feature extraction using frequency components becomes difficult, which results in difficulty in determining a proper size of the block.
In U.S. Pat. No. 6,078,697, entitled “Method and Apparatus for Segmenting Image Data into Contone, Text, and Halftone Classifications,” issued to Yee Seung Ng on Jun. 20, 2000, windows of predetermined sizes are set around all pixels of an input document image and then gradients of pixels in a corresponding window are calculated. Fuzzy probabilities to represent the probabilities that a central pixel will belong to a text area, a halftone image area, or a continuous tone area are calculated using the sizes and directions of the calculated gradients according to Fuzzy rules. Three Fuzzy probability values are compared, an area having the greatest Fuzzy probability value is determined as a class of the central pixel, and falsely-classified pixels are reclassified to fix (determine) a class of the central pixel. In this method, since the class of the central pixel is determined using only neighboring information, many errors may be made. In addition, when adjacent pixels belong to different classes, different image quality improvement methods should be applied to the adjacent pixels. As a result, a final print may be unpleasant to a viewer's eyes.
In U.S. Pat. No. 5,956,468, entitled “Document Segmentation System” and issued to Hakan Ancin on Sep. 21, 1999, an input document image is converted into a low resolution image, wide text and image areas are found from the low resolution image, and a dark text area on a bright background is found from the remaining area of the low resolution image to perform an image quality enhancement process to enhance the readability of the dark text area. In this method, only the dark text area on the bright background is emphasized, while an image area is hardly emphasized.